a specific subset of the natural nanomaterials.Women with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are at high risk of cardiovascular diseases (CVD). https://www.selleckchem.com/products/agomelatine-hydrochloride.html The atherogenic index of plasma (AIP) is a new marker for the assessment of CVD.
This study aimed to determine the predictive value of AIP with long term CVD risk among women with RA and SLE.
This is a cross-sectional study of 99 RA and 59 SLE women. Demographic, clinical, and biochemical data were obtained, and disease activities were calculated. For each patient, the long-term risk of CVD was calculated using the Framingham risk score (FRS); AIP was derived according to the logarithmic (triglycerides/high-density lipoproteins cholesterol).
The mean age of the RA and SLE patients was 47.97 ± 8.78 and 36.75 ± 9.09 years, respectively. The median (interquartile range) of AIP values in RA and SLE patients were 0.34 (-0.15, 1.02) and 0.33 (-0.53, 0.96), respectively, while FRS values of RA patients and SLE patients were 6.38 ± 5.58 and 4.86 ± 4.5, respectively (p &gt;0.05). There was a moderate correlation between AIP and FRS in RA and SLE patients (r=0.42, p=0.002 and r=0.33, p=0.007, respectively). According to the multivariate regression analyses, we found that AIP value is an independent factor for FRS in RA (β 4.13, 95% confidence interval; 1.71, 6.18; p=0.008) and in SLE patients (β 6.19, 95% confidence interval; 2.58, 9.81; p&lt;0.001).
We reported that AIP can be used as an independent indicator for long-term CVD risk in RA and SLE patients.
We reported that AIP can be used as an independent indicator for long-term CVD risk in RA and SLE patients.Hypoxic Preconditioning (HPC) has been well established to trigger endogenous mechanisms of neuroprotection basing on models of hypoxic and ischemic diseases in the Central Nervous System (CNS). However, its effects against Alzheimer's Disease (AD) still lack substantial evidence and in-depth exploration. The present study aimed to investigate the impacts of HPC on AD-related memory decline and amyloid-β (Aβ) pathology in AβPP/PS1 transgenic mice.
Seven-week-old AβPP/PS1 transgenic mice were randomized into HPC and non-HPC groups. The HPC groups were treated with early and repetitive HPC for four weeks, while the non-HPC group was raised under normoxia condition. All the animals were then raised until the age of 28 weeks when Morris water maze tests were conducted to examine the animals' spatial memory. Indicators for Aβ pathology (soluble Aβ levels and numbers of Aβ plaques) and the expression of relevant proteins were measured to explore potential mechanisms.
The results showed that HPC ameliorated memory decline and Aβ pathology in AβPP/PS1 mice. The protein levels of Amyloid-β Precursor Protein (AβPP) and β-site APP Cleaving Enzyme 1 (BACE1) were reduced while that of Hypoxic inducible factor 1α (HIF-1α) was elevated in HPC groups.
HPC might be a promising strategy for AD intervention. Its potential protection might be realized via downregulating the expressions of AβPP and BACE1 and hence inhibiting Aβ pathology. Notably, HIF-1α might play a key role in mediating subsequent neuroadaptive changes following HPC.
HPC might be a promising strategy for AD intervention. Its potential protection might be realized via downregulating the expressions of AβPP and BACE1 and hence inhibiting Aβ pathology. Notably, HIF-1α might play a key role in mediating subsequent neuroadaptive changes following HPC.Neuronal Microtubule (MT) tau protein, providing cytoskeleton to neuronal cells, plays a vital role, including maintenance of cell shape, intracellular transport, and cell division. Tau hyperphosphorylation mediated MT destabilization results in axonopathy, additionally neurotransmitter deficit and ultimately causing Alzheimer's disease. Pre-clinically, streptozotocin (3mg/kg, 10μl/ unilateral, ICV) stereotaxically mimics the behavioral and neurochemical alterations similar to Alzheimer's tau pathology resulting in MT assembly defects further lead to neuropathological cascades.
Clinically approved medications such as Donepezil (DNP), rivastigmine, and Memantine (MEM) are responsible for symptomatic care only, but there is no specific pharmacological intervention that directly interacts with the neuronal microtubule destabilization.
The current study focused on the involvement of anti-cancer agent microtubule stabilizer cabazitaxel at a low dose (0.5 and 2 mg/kg) alone and in combination with standard drugs DNP (5 mg/kg), MEM (10 mg/kg) and microtubule stabilizer Epothilone D (EpoD) (3 mg/kg) in the prevention of intracerebroventricular streptozotocin (ICV-STZ) intoxicated microtubule-associated tau protein hyperphosphorylation.
Chronic treatment of CBZ at a low dose alone and in combination with standard drugs showing no side effect and significantly improve the cognitive impairment, neurochemical alterations along with reducing the level of hyperphosphorylated tau by preventing the breakdown of the neuronal cytoskeleton, respectively.
The above findings suggested that CBZ at low dose show neuroprotective effects against ICV-STZ induced microtubule-associated tau protein hyperphosphorylation in rats and may be an effective agent for the preventive treatment of AD.
The above findings suggested that CBZ at low dose show neuroprotective effects against ICV-STZ induced microtubule-associated tau protein hyperphosphorylation in rats and may be an effective agent for the preventive treatment of AD.Stem cells (SCs) show a wide range of applications in the treatment of numerous diseases including neurodegenerative diseases, diabetes, cardiovascular diseases, cancer, etc. SC related research has gained popularity owing to the unique characteristics of self-renewal and differentiation. Artificial intelligence (AI), an emerging field of computer science and engineering has shown potential applications in different fields like robotics, agriculture, home automation, healthcare, banking, and transportation since its invention. This review aims to describe the various applications of AI in SC biology including understanding the behavior of SCs, recognizing individual cell type before undergoing differentiation, characterization of SCs using mathematical models and prediction of mortality risk associated with SC transplantation. This review emphasizes the role of neural networks in SC biology and further elucidates the concepts of machine learning and deep learning and their applications in SC research.